- Adaptive Monte-Carlo Localization
- Robotics Inference
- Traffic Light Detector
- Perception and Mapping: a "search, sample, and return project" with a virtual rover.
- I used a fully-convolutional neural network to paint all pixels in an image which is part of a person. Two types of persons are identified, the “hero” target person, and everyone else.
- Localization using Histogram Filter Algorithm
- A catkin workspace in ROS where a virtual PR2 Robot with an RGBD camera perceives objects and places them on the appropriate dropbox.
- A catkin workspace in ROS that capture features of objects and then train a classifier to correctly identify the objects from a point cloud file.
- A small collection of toys to demonstrate PID control concepts.
- Particle Filters and Kidnapped Vehicle Project
- A particle-filter visualization in Python using Bokeh based on Udacity's free A.I. for Robotics course
- A particle filter implementation to track a kidnapped robot.
- Inverse Kinematics Arm
- An Inverse Kinematics 6DOF Robot Arm Pick and Place Project in ROS.
- Point Cloud Filter
- Scripts showcasing filtering techniques applied to point cloud data.
- Point Cloud Clusters
- A catkin workspace in ROS which uses DBSCAN to identify which points in a point cloud belong to the same object.
- Highway Path Planning
- My path-planning pipeline to navigate a car safely around a virtual highway with other traffic.
- Model Predictive Control
- A software pipeline using the Model Predictive Control method to drive a car around a virtual track.
- Semantic Segmentation
- A Fully Convolutional Network (FCN) script to label the pixels of a road in images
- Traffic Sign Classification
- A deep neural network to classify traffic signs, using TensorFlow.
- Unscented Kalman Filter
- An unscented Kalman Filter implementation in C++ for fusing lidar and radar sensor measurements.
- Extended Kalman Filter
- An extended Kalman Filter implementation in C++ for fusing lidar and radar sensor measurements.
- Vehicle Tracking
- A vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM).
- Advanced Lane Detection
- An advanced lane-finding algorithm using distortion correction, image rectification, color transforms, and gradient thresholding.